Holly S. R. Jones

Assessment of player’s postural control following a lower limb injury is of interest to sports medicine practitioners due to its fundamental role in daily tasks and sporting activities. The aim was to longitudinally monitor professional rugby union players’ postural control during each phase of the rehabilitation program (acute, middle, and late) following a lower limb injury. Seven male rugby union players (height 1.80 [0.02] m; mass 100.3 [11.4] kg; age 24 [4] y) sustained a time loss, noncontact lower limb injury. Static postural control was assessed via sway path (in meters), and dynamic postural control was assessed via vertical postural stability index. Group differences (P < .05) were reported across the acute, middle, and late phase. Smaller magnitudes of sway path were observed for eyes-open sway path, and for the middle and late phase smaller magnitudes of vertical postural stability index (P < .05) at the end session compared with first session. Whereas larger magnitudes of vertical postural stability index were found between baseline and the last session (P < .05). Large interindividual and intraindividual variation was apparent across the 3 phases of rehabilitation. Postural control improvements were identified during rehabilitation. However, postural control did not return to baseline, with altered kinetics throughout each rehabilitation phase.

Given the high rates of both primary and secondary anterior cruciate ligament (ACL) injuries in multidirectional field sports, there is a need to develop easily accessible methods for practitioners to monitor ACL injury risk. Field-based methods to assess knee variables associated with ACL injury are of particular interest to practitioners for monitoring injury risk in applied sports settings. Knee variables or proxy measures derived from wearable inertial measurement units (IMUs) may thus provide a powerful tool for efficient injury risk management. Therefore, the aim of this study was to identify whether there were correlations between laboratory-derived knee variables (knee range of motion (RoM), change in knee moment, and knee stiffness) and metrics derived from IMUs (angular velocities and accelerations) placed on the tibia and thigh, across a range of movements performed in practitioner assessments used to monitor ACL injury risk. Ground reaction forces, three-dimensional kinematics, and triaxial IMU data were recorded from nineteen healthy male participants performing bilateral and unilateral drop jumps, and a 90° cutting task. Spearman’s correlations were used to examine the correlations between knee variables and IMU-derived metrics. A significant strong positive correlation was observed between knee RoM and the area under the tibia angular velocity curve in all movements. Significant strong correlations were also observed in the unilateral drop jump between knee RoM, change in knee moment, and knee stiffness, and the area under the tibia acceleration curve (r_s = 0.776, r_s = −0.712, and r_s = −0.765, respectively). A significant moderate correlation was observed between both knee RoM and knee stiffness, and the area under the thigh angular velocity curve (r_s = 0.682 and r_s = −0.641, respectively). The findings from this study suggest that it may be feasible to use IMU-derived angular velocities and acceleration measurements as proxy measures of knee variables in movements included in practitioner assessments used to monitor ACL injury risk.

There are currently a multitude of tests used to assess readiness to return to sport (RTS) following anterior cruciate ligament reconstruction (ACLR). The aim of this study was to establish the extent to which movement strategies transfer between three common assessment tasks to help improve design of athlete testing batteries following ACLR. A cohort of 127 male patients 8–10 months post‐ACLR and 45 non‐injured controls took part in the study. Three movement tasks were completed (unilateral and bilateral drop jump, and 90° pre‐planned cut), while ground reaction forces and three‐dimensional kinematics (250 Hz) were recorded. Compared to the bilateral drop jump and cut, the unilateral drop jump had a higher proportion of work done at the ankle (d = 0.29, p < 0.001 and d = −1.87, p < 0.001, respectively), and a lower proportion of work done at the knee during the braking phase of the task (d = 0.447, p < 0.001 and d = 1.56, p < 0.001, respectively). The ACLR group had higher peak hip moments than the non‐injured controls, although the proportion of work done at the ankle, knee and hip joints were similar. Movement strategies were moderately and positively related at the ankle (r_s = 0.728, p < 0.001), knee (r_s = 0.638, p < 0.001) and hip (r_s = 0.593, p < 0.001) between the unilateral and bilateral drop jump, but there was no relationship at the ankle (r_s = 0.10, p = 0.104), knee (r_s = 0.106, p = 0.166) and hip (r_s = −0.019, p = 0.808) between the unilateral drop jump and the cut. Clinicians could therefore consider omitting one of the drop jumps from assessment batteries but should include both jumping and cutting tasks.